Estimating the threshold of health workforce densities towards universal health coverage in Africa. (19th May 2022)

• Record Type: Journal Article
• Authors: Ahmat, Adam; Asamani, James Avoka; Abdou Illou, Mourtala Mahaman; Millogo, Jean Jacques Salvador; Okoroafor, Sunny C; Nabyonga-Orem, Juliet; Karamagi, Humphrey Cyprian; Nyoni, Jennifer
• Is Part Of: BMJ global health. Volume 7(2022)Supplement 1
• Publication Date: 2022-05-19
• Subjects: Human Resources for Health -- Threshold density -- HRH planning -- Health workforce density -- Universal Health Coverage (UHC) service index -- structural equation model -- Reduced Gradient (GRG) approach -- Africa; World health -- Periodicals; 362.105
• DOI: 10.1136/bmjgh-2021-008310
• Languages: English
• ISSNs: 2059-7908

Abstract

Abstract : Background: There have been past efforts to develop benchmarks for health workforce (HWF) needs across countries which have been helpful for advocacy and planning. Still, they have neither been country-specific nor disaggregated by cadre—primarily due to data inadequacies. This paper presents an analysis to estimate a threshold of 13 cadres of HWF density to support the progressive realisation of universal health coverage (UHC). Method: Using UHC service coverage as the outcome measure, a two-level structural equation model was specified and analysed in STATA V.16. In the first level of structural equations, health expenditure per capita—one of the cross-cutting inputs for UHC, was used to explain the critical inputs for service delivery/coverage. In the second level of the model, the critical inputs for service delivery were used to explain the UHC Service Coverage Index (UHC SCI), in which the contribution of the HWF was 'partial out'. Results: The analysis found that a unit increase in the HWF density per 10 000 population is positively associated with statistically significant improvements in the UHC SCI of countries (β=0.127, p<0.001). Similarly, a positive and statistically significant association was established between diagnostic readiness and the UHC SCI (β=0.243, p=0.015). Essential medicines readiness was positively correlated but not statistically significant (β=0.053, p=0.658). Controlling for other variables, a density of 134.23 per 10 000 population across 13 HWF categories is necessary to attain at least 70% UHC SCI. Conclusion: Consistent with current knowledge, the HWF is a significant predictor of the UHC SCI. Attaining at least 70% of the UHC SCI requires about 134.23 health workers (a mix of 13 cadres) per 10 000 population.